12, 21–25 (2014)īillings, G., Johnson-Roberson, M.: SilhoNet-fisheye: adaptation of a ROI based object pose estimation network to monocular fisheye images. Gim, Y., Ko, H.S., et al.: Study on correction of optical distortion for flow visualization inside axisymmetric droplet. Wei, L., et al.: Double longitude model based correction method for fisheye image distortion. Lijun, L., Meng, L., Ye, S.: Correction method of image distortion of fisheye lens. Zhang, Z.: A flexible new technique for camera calibration. Compared with the traditional ORB (Oriented FAST and Rotated BRIEF) method, the FAST-MIS stitching algorithm proposed in this paper can shorten the time of image stitch by about 23%. Through experiment results shows that the error of the accurate correction algorithm proposed in this paper is reduced compared with the traditional method, and the correction effect of the result is also improved. The algorithm proposed in this paper transforms the feature points in the process of large-size image Mosaic into small-size image feature points, which reduces the screening range of feature band, thus speeding up the screening speed and accuracy of effective feature points. In this paper, we use FAST-MIS (Fast multi-image stitching) stitching algorithm to quickly stitch multiple photographs. First of all, for correcting the fisheye image, this paper presents a accurate correction algorithm, which produces fewer errors and results in better image quality. To implement this process, this paper proposes a fisheye image stitching algorithm include an accurate correction algorithm and a FAST-MIS stitching method to correction and stitch the fisheye image, finally obtain the stitch panoramic image. The application of underwater vehicles is an important link in the process of detecting marine resources, in the process, it is necessary to correct underwater images and stitch corrected images to receive a panoramic image.
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